Staff Machine Learning Engineer Jobs

Staff Machine Learning Engineer

Orbis Consultants

Location:
United States, Austin

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

Are you excited by the challenge of pushing the boundaries of what modern AI models can do – especially when data is limited? A fast-growing AI platform is looking for a Staff Machine Learning Engineer to help shape the next generation of large-scale intelligent systems. In this role, you’ll take the lead on developing advanced Large Language Models (LLMs) and Mixture-of-Experts (MoE) architectures, driving innovation that directly influences product capabilities and performance. If you thrive at the intersection of research and real-world impact, you’ll feel right at home here.

Job Responsibility:

Architect, train, and optimize cutting-edge LLMs and MoE-based systems
Experiment with novel algorithms to improve efficiency, scalability, and model performance
Collaborate closely with engineering and product teams to deploy ML capabilities into production
Contribute to pioneering research in ML and NLP, driving methodological advancements
Mentor engineers and help shape technical best practices across the organisation

Requirements:

Advanced degree in Computer Science or a related field (PhD preferred)
6+ years of industry experience building and deploying machine learning models at scale
Deep expertise in LLMs, Mixture-of-Experts architectures, and modern ML frameworks such as PyTorch or TensorFlow
Demonstrated innovation through impactful research, patents, or production-grade ML systems
Ability to lead complex, cross-functional technical initiatives
Strong problem-solving skills and a passion for pushing the boundaries of AI

Nice to have:

Publications or conference presentations at leading ML/NLP venues such as NeurIPS, ICML, ICLR, AAAI, EMNLP, NACL, ACL, EACL, CoNLL, or similar
Experience with cloud platforms (AWS, Azure, GCP) and distributed computing tools (Spark, Hadoop)
Familiarity with containerization and orchestration (Docker, Kubernetes)

What we offer:

Competitive compensation and performance incentives
Comprehensive medical, dental, and vision benefits
Monthly wellness stipend + annual continuing education credit
A flexible work environment and unlimited approved PTO
Parental and bereavement leave and other employee support programs
Relocation support available

Additional Information:

Job Posted:
December 11, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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